This study aimed to develop an algorithm to automatically extract annotations
for chest X-ray classification models from German thoracic radiology reports.
An automatic label extraction model was designed based on the CheXpert
architecture, and a web-based annotation interface was created for iterative
improvements. Results showed that automated label extraction can reduce time
spent on manual labeling and improve overall modeling performance. The model
trained on automatically extracted labels performed competitively to manually
labeled data and strongly outperformed the model trained on publicly available
data.

本研究旨在开发一种算法，用于自动从德国胸腔放射学报告中提取用于 X 光分类模型注释的标签，并基于 CheXpert 架构设计了一个自动标注提取模型，并创建了一个基于 Web 的注释界面以进行迭代改进，结果表明，自动标签提取能够减少手动标注的时间并提高整体建模性能。与手动标记数据相比，使用自动提取标签训练的模型表现出了很高的竞争力，并且强大地优于使用公开数据训练的模型。